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Demographics | Physical health | Hearing | Cognition | Mobility and balance | Quality of life | Mental health | Social participation and support | Views on hearing loss |


Background

Why impute missing data?

Logistic regression and other statistical methods require complete cases. In our case, with 40+ variables of interest, dropping participants with any missing values leads to a sample size of 200+ cases instead of 500+. There is loss of power, and estimates from models will likely be biased. The goal of missing data imputation is to restore variance of the sample to make it better reflect characteristics of the population (i.e., give accurate estimates of standard errors, CI’s, and p-values).

MICE procedure

  1. Say there are three variables ‘A’, ‘B’, and ‘C’, each with some missing values. Choose variable ‘A’ to start filling in. Fill in missing values in ‘B’ and ‘C’ with temporary values, such as the mean.

  2. Predict missing ‘A’, using A ~ B + C, adding a random component. Move on to predicting missing ‘B’, using B ~ A + C and including predicted ‘A’, again adding a random component. Move on to predicting missing ‘C’, using C ~ A + B and predicted ‘B’. This is one cycle.

  3. Choose the number of cycles, say 10 iterations. At the end of 10 iterations, an “imputed” dataset is formed with complete cases. Choose the number of imputed datasets to form (the same analysis will be conducted on each slightly different dataset, and the results will be pooled). Choose which variables should be used as predictors of other variables. Choose which method to use for predicting missing values, e.g., predictive mean matching. For derived variables such as summed scores, consider whether to impute components first and then calculate derived scores, or impute derived scores. Consider whether there should be an order of which variables to start imputing first.

  4. Check whether the imputed data “converge” (the means and SEs stabilize after a few iterations, and are similar across imputed datasets). Check the distributions and characteristics of imputed data (e.g. integer-only values, floors and ceilings, plausibility), and their similarity to observed data.


1. Pre-imputation work

(i) Evaluate missingness

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Variables of interest Demographics: Age, Gender, Work, Volunteer, Live alone
Physical health: Rating, Multimorbidity score, Subjective vision (loss, rating aided), Subjective hearing (loss, rating aided, rating unaided)
Hearing health: Hearing device use, Hearing device type, Tinnitus past 7 days, 15i-SSQ mean score, SIM mean score, EmoCheQ mean score, HHIE-S total score, BPTA4
Cognitive health: Subjective cognitive impairment, CSRQ mean score
Mobility and balance: Mobility aid, ABC mean score
Quality of life: SWLS mean score, WHO overall QoL, WHO health QoL, WHO money, WHO four domains
Mental health: PHQ mean score
Social factors: Loneliness, Social Network Index, Social Participation Frequency, Social Participation Types, Social Support MOS mean score
Views: Connections total correct score, Motivations mean score
% Missing data within participants
## 
##   The decimal point is at the |
## 
##    0 | 00004444444444444444444444444444444444444999999999999999999999999999+193
##    2 | 22222222222222222222222222222222222222222277777777777777777777777777+16
##    4 | 000044444999993333333888888888888
##    6 | 222222222222222666666666666666666111111111111111111155555555555
##    8 | 0000000004444888833337777
##   10 | 221199
##   12 | 488
##   14 | 2055
##   16 | 47
##   18 | 65
##   20 | 
##   22 | 5
##   24 | 2
##   26 | 
##   28 | 
##   30 | 
##   32 | 
##   34 | 
##   36 | 
##   38 | 
##   40 | 
##   42 | 9
##   44 | 
##   46 | 
##   48 | 
##   50 | 
##   52 | 
##   54 | 
##   56 | 
##   58 | 
##   60 | 6
##   62 | 
##   64 | 6
##   66 | 87
##   68 | 
##   70 | 8827
##   72 | 6
##   74 | 337
##   76 | 0
##   78 | 
##   80 | 5
##   82 | 
##   84 | 
##   86 | 
##   88 | 
##   90 | 6
##   92 | 
##   94 | 
##   96 | 
##   98 | 66
Missing data patterns


Participants with <26% missing data (n=509):


Participants with >42% missing data (n=18):


(ii) Data cleaning

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Rules
  • For “single-item” variables (e.g. loneliness): NA’s are left as is.
  • For co-morbidity checklist: All responses other than “yes” (NA’s, No, Don’t know) are treated as “no”.
  • For composite variables: If a participant has “NA” for all items, the composite score is also “NA”.
  • WHOQOL-BREF: Follow their protocol for NA’s.
  • For SIM, EmoCheQ, CSRQ, PHQ4, Views on motivations: Impute case mean.
  • For 15i-SSQ: Impute case mean within subscale.
  • For HHIES: Impute case mode within subscale.
  • For ABC: Recode NA’s to 0 (single participant).
  • For Social Network Index: Recode NA’s to “never”.
  • For Social Participation: Recode NA’s to “never”.
  • For Social Support: Recode NA’s to “none”.
  • For Views (Connections): Drop foil item; only correct items credited.
  • For Views (Motivations): Impute mean.


Cleaning details


(iii) Evaluate missingness again

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% Missing data within participants
## 
##   The decimal point is at the |
## 
##    0 | 00000000000000000000000000000000000000000000000000000000000000000000+152
##    2 | 33333333333333333333333333333333333333333333333333333333333333333333+50
##    4 | 555555555555555555555555555555555555555555555
##    6 | 88888888888888888888888888888888888888888888888888888888888
##    8 | 1111111111111111111111111
##   10 | 444444444444
##   12 | 6666
##   14 | 9
##   16 | 
##   18 | 2
##   20 | 
##   22 | 
##   24 | 
##   26 | 
##   28 | 
##   30 | 
##   32 | 
##   34 | 
##   36 | 
##   38 | 6
##   40 | 
##   42 | 
##   44 | 
##   46 | 7
##   48 | 
##   50 | 00
##   52 | 3
##   54 | 
##   56 | 8888
##   58 | 111
##   60 | 
##   62 | 6
##   64 | 
##   66 | 
##   68 | 2
##   70 | 5
##   72 | 
##   74 | 0
##   76 | 
##   78 | 
##   80 | 
##   82 | 
##   84 | 
##   86 | 
##   88 | 
##   90 | 99
Missing data patterns


Participants with <20% missing data (n=509):

## # A tibble: 44 × 3
##    variable                    n_miss pct_miss
##    <chr>                        <int>    <num>
##  1 Gender_bin                       0    0    
##  2 Age                              2    0.393
##  3 Retired_bin                      0    0    
##  4 Volunteer                        0    0    
##  5 Lives_alone_bin                  0    0    
##  6 Phys_health_rating               7    1.38 
##  7 Multimorbidity_score             0    0    
##  8 Subj_vision_loss_bin            18    3.54 
##  9 Subj_vision_rating_aided         1    0.196
## 10 Subj_hearing_loss_bin           36    7.07 
## 11 any_hearing_device               0    0    
## 12 study2_HA                        0    0    
## 13 Subj_hearing_rating_aided      159   31.2  
## 14 Subj_hearing_rating_unaided      8    1.57 
## 15 Tinnitus_past_wk_bin             0    0    
## 16 ssq_speech                      46    9.04 
## 17 ssq_spatial                     51   10.0  
## 18 ssq_qualities                    3    0.589
## 19 SIM_mean                        12    2.36 
## 20 Emocheq_mean                     8    1.57 
## 21 hhies_emo_total                  0    0    
## 22 hhies_soc_total                  0    0    
## 23 positive_SCI_bin                 0    0    
## 24 CSRQ_mean                        0    0    
## 25 Mobility_needs_bin               0    0    
## 26 ABC_mean                         0    0    
## 27 SWLS_mean                        0    0    
## 28 WHOQOL_overall_qol               0    0    
## 29 WHOQOL_health_qol                0    0    
## 30 WHOQOL_Dom1_phys                 0    0    
## 31 WHOQOL_Dom2_psy                  0    0    
## 32 WHOQOL_Dom3_soc                  1    0.196
## 33 WHOQOL_Dom4_env                  0    0    
## 34 WHO_money                        0    0    
## 35 PHQ4_mean                        1    0.196
## 36 Lonely_bin                       1    0.196
## 37 Social_network_index             1    0.196
## 38 Soc_part_freq                    1    0.196
## 39 Soc_part_types                   1    0.196
## 40 Connections_total                9    1.77 
## 41 Motivate_mean                    5    0.982
## 42 HA.Purchase                     78   15.3  
## 43 PTA4_better_ear                 73   14.3  
## 44 PTA4_asym                       74   14.5


Participants with >39%% missing data (n=18):

## # A tibble: 43 × 3
##    variable                    n_miss pct_miss
##    <chr>                        <int>    <num>
##  1 Gender_bin                       2     11.1
##  2 Age                              3     16.7
##  3 Retired_bin                      2     11.1
##  4 Volunteer                        2     11.1
##  5 Lives_alone_bin                  2     11.1
##  6 Phys_health_rating               4     22.2
##  7 Multimorbidity_score             0      0  
##  8 Subj_vision_loss_bin             4     22.2
##  9 Subj_vision_rating_aided         4     22.2
## 10 Subj_hearing_loss_bin            5     27.8
## 11 any_hearing_device               0      0  
## 12 study2_HA                        0      0  
## 13 Subj_hearing_rating_aided       10     55.6
## 14 Subj_hearing_rating_unaided      5     27.8
## 15 Tinnitus_past_wk_bin             0      0  
## 16 ssq_speech                      15     83.3
## 17 ssq_spatial                     13     72.2
## 18 ssq_qualities                    8     44.4
## 19 SIM_mean                        13     72.2
## 20 Emocheq_mean                    13     72.2
## 21 hhies_emo_total                 15     83.3
## 22 hhies_soc_total                 15     83.3
## 23 positive_SCI_bin                15     83.3
## 24 CSRQ_mean                       17     94.4
## 25 Mobility_needs_bin              17     94.4
## 26 ABC_mean                        17     94.4
## 27 SWLS_mean                       17     94.4
## 28 WHOQOL_overall_qol              18    100  
## 29 WHOQOL_health_qol               18    100  
## 30 WHOQOL_Dom1_phys                18    100  
## 31 WHOQOL_Dom2_psy                 18    100  
## 32 WHOQOL_Dom3_soc                 18    100  
## 33 WHOQOL_Dom4_env                 18    100  
## 34 WHO_money                       18    100  
## 35 PHQ4_mean                       18    100  
## 36 Lonely_bin                      18    100  
## 37 Social_network_index            18    100  
## 38 Soc_part_freq                   18    100  
## 39 Soc_part_types                  18    100  
## 40 Connections_total               18    100  
## 41 Motivate_mean                   18    100  
## 42 HA.Purchase                      5     27.8
## 43 PTA4_better_ear                  5     27.8


Complete cases out of n=527 (none of 44 variables missing):

## [1] 232
## [1] 44.02277


(iv) Justify discarding participants

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Drop 2 cases that are fully missing
## # A tibble: 44 × 3
##    variable                    n_miss pct_miss
##    <chr>                        <int>    <num>
##  1 Gender_bin                       2      100
##  2 Age                              2      100
##  3 Retired_bin                      2      100
##  4 Volunteer                        2      100
##  5 Lives_alone_bin                  2      100
##  6 Phys_health_rating               2      100
##  7 Multimorbidity_score             0        0
##  8 Subj_vision_loss_bin             2      100
##  9 Subj_vision_rating_aided         2      100
## 10 Subj_hearing_loss_bin            2      100
## 11 any_hearing_device               0        0
## 12 study2_HA                        0        0
## 13 Subj_hearing_rating_aided        2      100
## 14 Subj_hearing_rating_unaided      2      100
## 15 Tinnitus_past_wk_bin             0        0
## 16 ssq_speech                       2      100
## 17 ssq_spatial                      2      100
## 18 ssq_qualities                    2      100
## 19 SIM_mean                         2      100
## 20 Emocheq_mean                     2      100
## 21 hhies_emo_total                  2      100
## 22 hhies_soc_total                  2      100
## 23 positive_SCI_bin                 2      100
## 24 CSRQ_mean                        2      100
## 25 Mobility_needs_bin               2      100
## 26 ABC_mean                         2      100
## 27 SWLS_mean                        2      100
## 28 WHOQOL_overall_qol               2      100
## 29 WHOQOL_health_qol                2      100
## 30 WHOQOL_Dom1_phys                 2      100
## 31 WHOQOL_Dom2_psy                  2      100
## 32 WHOQOL_Dom3_soc                  2      100
## 33 WHOQOL_Dom4_env                  2      100
## 34 WHO_money                        2      100
## 35 PHQ4_mean                        2      100
## 36 Lonely_bin                       2      100
## 37 Social_network_index             2      100
## 38 Soc_part_freq                    2      100
## 39 Soc_part_types                   2      100
## 40 Connections_total                2      100
## 41 Motivate_mean                    2      100
## 42 HA.Purchase                      2      100
## 43 PTA4_better_ear                  2      100
## 44 PTA4_asym                        2      100
Retain 16 that mostly have age, audiogram, earlier measures
## # A tibble: 44 × 3
##    variable                    n_miss pct_miss
##    <chr>                        <int>    <num>
##  1 Gender_bin                       0     0   
##  2 Age                              1     6.25
##  3 Retired_bin                      0     0   
##  4 Volunteer                        0     0   
##  5 Lives_alone_bin                  0     0   
##  6 Phys_health_rating               2    12.5 
##  7 Multimorbidity_score             0     0   
##  8 Subj_vision_loss_bin             2    12.5 
##  9 Subj_vision_rating_aided         2    12.5 
## 10 Subj_hearing_loss_bin            3    18.8 
## 11 any_hearing_device               0     0   
## 12 study2_HA                        0     0   
## 13 Subj_hearing_rating_aided        8    50   
## 14 Subj_hearing_rating_unaided      3    18.8 
## 15 Tinnitus_past_wk_bin             0     0   
## 16 ssq_speech                      13    81.2 
## 17 ssq_spatial                     11    68.8 
## 18 ssq_qualities                    6    37.5 
## 19 SIM_mean                        11    68.8 
## 20 Emocheq_mean                    11    68.8 
## 21 hhies_emo_total                 13    81.2 
## 22 hhies_soc_total                 13    81.2 
## 23 positive_SCI_bin                13    81.2 
## 24 CSRQ_mean                       15    93.8 
## 25 Mobility_needs_bin              15    93.8 
## 26 ABC_mean                        15    93.8 
## 27 SWLS_mean                       15    93.8 
## 28 WHOQOL_overall_qol              16   100   
## 29 WHOQOL_health_qol               16   100   
## 30 WHOQOL_Dom1_phys                16   100   
## 31 WHOQOL_Dom2_psy                 16   100   
## 32 WHOQOL_Dom3_soc                 16   100   
## 33 WHOQOL_Dom4_env                 16   100   
## 34 WHO_money                       16   100   
## 35 PHQ4_mean                       16   100   
## 36 Lonely_bin                      16   100   
## 37 Social_network_index            16   100   
## 38 Soc_part_freq                   16   100   
## 39 Soc_part_types                  16   100   
## 40 Connections_total               16   100   
## 41 Motivate_mean                   16   100   
## 42 HA.Purchase                      3    18.8 
## 43 PTA4_better_ear                  3    18.8 
## 44 PTA4_asym                        3    18.8


(v) Variable relationships

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Correlations heatmap: Hearing
Correlations heatmap: Physical health
Simple correlations using quickpred( )

Choosing predictors based on simple correlations

PCA


2. Imputation using MICE

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Method:
* predictors that correlate 0.5 or better; if no such predictors, adjust threshold to 0.4, then 0.3
* total of 5 imputed datasets, with a maximum of 10 iterations per dataset


3. Results from complete cases vs. imputed data

Predicting hearing aid adoption

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Note: Not filtered by hearing aid candidacy according to threshold(s) at 2kHz.

Complete cases only (n=257)

Non-hearing aid users = 166
Hearing aid users = 80


Significant predictors: Subj_hearing_rating_aided, Subj_hearing_rating_unaided, SWLS_mean, PTA4_better_ear
“Borderline”: SSQ15i_mean, SWLS_mean

## 
## Call:
## glm(formula = formula_adopt, family = "binomial", data = compdata_ad)
## 
## Coefficients:
##                                Estimate  Std. Error z value   Pr(>|z|)    
## (Intercept)                  -32.741259 1452.817468  -0.023    0.98202    
## Gender_bin                     1.595429    1.040222   1.534    0.12509    
## Age                           -0.064929    0.063040  -1.030    0.30303    
## Retired_bin                    0.266908    1.063635   0.251    0.80186    
## Volunteer_rec                  0.898904    0.539164   1.667    0.09547 .  
## Lives_alone_bin               -1.202422    1.152395  -1.043    0.29676    
## Phys_health_rating             0.396070    0.782182   0.506    0.61260    
## Multimorbidity_score           0.282669    0.246895   1.145    0.25225    
## Subj_vision_rating_aided      -0.652282    0.608955  -1.071    0.28410    
## Subj_hearing_loss_bin         18.953453 1452.771718   0.013    0.98959    
## Subj_hearing_rating_aided      4.410219    0.934386   4.720 0.00000236 ***
## Subj_hearing_rating_unaided   -3.678818    0.939617  -3.915 0.00009032 ***
## Tinnitus_past_wk_bin          -0.405308    0.763624  -0.531    0.59558    
## SSQ15i_mean                    0.687075    0.375327   1.831    0.06716 .  
## SIM_mean                       0.131242    0.269486   0.487    0.62625    
## Emocheq_mean                  -0.469772    0.602305  -0.780    0.43542    
## HHIES_total                   -0.007491    0.076414  -0.098    0.92191    
## positive_SCI_bin               0.003053    1.276869   0.002    0.99809    
## CSRQ_mean                      0.595525    1.230241   0.484    0.62834    
## Mobility_needs_bin            -0.806893    2.067784  -0.390    0.69637    
## ABC_mean                      -0.045911    0.056297  -0.816    0.41478    
## SWLS_mean                      1.264797    0.666152   1.899    0.05761 .  
## WHOQOL_overall_qol            -0.849883    0.879340  -0.967    0.33379    
## WHOQOL_health_qol              0.033379    0.671457   0.050    0.96035    
## WHO_money                      0.977226    0.627806   1.557    0.11957    
## PHQ4_mean                      0.812446    1.016468   0.799    0.42413    
## Lonely_bin                     2.348070    1.591187   1.476    0.14003    
## Social_network_index          -0.276936    0.401326  -0.690    0.49016    
## Soc_part_freq                  0.403448    0.662299   0.609    0.54242    
## Soc_part_types                 0.114114    0.411978   0.277    0.78179    
## Motivate_mean                 -0.882616    0.603671  -1.462    0.14372    
## PTA4_better_ear                0.164242    0.061936   2.652    0.00801 ** 
## PTA4_asym                      0.065309    0.043998   1.484    0.13771    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## (Dispersion parameter for binomial family taken to be 1)
## 
##     Null deviance: 310.319  on 245  degrees of freedom
## Residual deviance:  70.645  on 213  degrees of freedom
## AIC: 136.64
## 
## Number of Fisher Scoring iterations: 19
With missing data imputation (n=525)


Significant predictors: Volunteering, Subj_hearing_rating_aided, Subj_hearing_rating_unaided, SSQ15i_mean, ABC_mean (balance), PHQ4_mean (anxiety & depression), PTA4_better_ear

“Borderline”: Subj_hearing_loss_bin, SWLS_mean, PTA4_asym

##                           term      estimate   std.error   statistic        df
## 1                  (Intercept) -0.8069314818 0.347688012 -2.32084930 221.99196
## 2                   Gender_bin  0.0213103466 0.035588740  0.59879463 181.13383
## 3                          Age  0.0030946174 0.002458405  1.25879050 147.67164
## 4                  Retired_bin -0.0329322640 0.034810440 -0.94604561 373.95398
## 5                Volunteer_rec  0.0384696492 0.021014378  1.83063465 102.98698
## 6              Lives_alone_bin -0.0421223132 0.040621309 -1.03695114 108.10358
## 7           Phys_health_rating  0.0048974761 0.024822393  0.19730072 479.64343
## 8         Multimorbidity_score  0.0010202011 0.007497715  0.13606826 221.41715
## 9     Subj_vision_rating_aided -0.0014353804 0.022066377 -0.06504831 364.36256
## 10       Subj_hearing_loss_bin  0.0844530941 0.055600558  1.51892529  32.82621
## 11   Subj_hearing_rating_aided  0.1689107116 0.026451476  6.38568202  14.66008
## 12 Subj_hearing_rating_unaided -0.1857980295 0.028057215 -6.62211243  95.78959
## 13        Tinnitus_past_wk_bin -0.0233440561 0.034242844 -0.68172072 195.88066
## 14                 SSQ15i_mean  0.0340272696 0.014147564  2.40516816 113.40805
## 15                    SIM_mean -0.0003149891 0.007511506 -0.04193422 455.56254
## 16                Emocheq_mean -0.0030424740 0.019886497 -0.15299195 406.62382
## 17                 HHIES_total  0.0033770670 0.002734797  1.23485128 346.69664
## 18            positive_SCI_bin  0.0448430673 0.053323627  0.84096057 352.29619
## 19                   CSRQ_mean -0.0170251042 0.046529860 -0.36589631 346.04220
## 20          Mobility_needs_bin -0.0385328494 0.080872256 -0.47646562 212.81316
## 21                    ABC_mean -0.0026130143 0.001687901 -1.54808532  76.55505
## 22                   SWLS_mean  0.0282781959 0.018999204  1.48838842 125.90802
## 23          WHOQOL_overall_qol  0.0026437000 0.037230582  0.07100883  53.51686
## 24           WHOQOL_health_qol  0.0231610629 0.023214441  0.99770065 101.98604
## 25                   WHO_money  0.0202992253 0.021711638  0.93494673  31.69368
## 26                   PHQ4_mean  0.1057386289 0.039162194  2.70001802 323.42657
## 27                  Lonely_bin -0.0222851838 0.044412033 -0.50178257 264.69183
## 28        Social_network_index -0.0043010248 0.013630313 -0.31554850 170.09644
## 29               Soc_part_freq  0.0111070032 0.025880134  0.42917101 348.56966
## 30              Soc_part_types -0.0055868731 0.012025513 -0.46458501 306.53098
## 31               Motivate_mean  0.0139793267 0.018237954  0.76649643 417.41902
## 32             PTA4_better_ear  0.0062904258 0.002357231  2.66856575  30.77204
## 33                   PTA4_asym  0.0028221170 0.001372063  2.05684188 268.72822
##              p.value
## 1  0.021202335223233
## 2  0.550057952873636
## 3  0.210092352772850
## 4  0.344736207353346
## 5  0.070046775338566
## 6  0.302072561198147
## 7  0.843675794718204
## 8  0.891890945202822
## 9  0.948171212636370
## 10 0.138355038748211
## 11 0.000013642781195
## 12 0.000000002051981
## 13 0.496220804627005
## 14 0.017782907611612
## 15 0.966569508762473
## 16 0.878480511227692
## 17 0.217722090998015
## 18 0.400940446495265
## 19 0.714666027216855
## 20 0.634231525301153
## 21 0.125726032185143
## 22 0.139148870536759
## 23 0.943655425709040
## 24 0.320785858070180
## 25 0.356885099935214
## 26 0.007298342454854
## 27 0.616237592331074
## 28 0.752732052336673
## 29 0.668063909362946
## 30 0.642558482578352
## 31 0.443814231253736
## 32 0.012044452103685
## 33 0.040666695793303


Predicting subjective hearing loss

Complete cases only (n=246)

Significant predictors: Lives_alone, Phys_health_rating, Subj_hearing_rating_unaided, HHIES_total, Social_network_index

“Borderline”: Gender, Multimorbidity, Tinnitus_past_wk_bin, WHOQOL_health_qol

## 
## Call:
## glm(formula = formula_subj, family = "binomial", data = compdata_subj)
## 
## Coefficients:
##                             Estimate Std. Error z value Pr(>|z|)    
## (Intercept)                  7.20205   11.32644   0.636 0.524866    
## Gender_bin                   2.31782    1.24407   1.863 0.062448 .  
## Age                          0.09764    0.07394   1.321 0.186665    
## Retired_bin                  0.50181    1.03681   0.484 0.628389    
## Volunteer_rec               -0.25097    0.52291  -0.480 0.631258    
## Lives_alone_bin              3.55977    1.40448   2.535 0.011258 *  
## Phys_health_rating           2.49657    1.06599   2.342 0.019180 *  
## Multimorbidity_score         0.48840    0.26459   1.846 0.064915 .  
## Subj_vision_rating_aided     0.77191    0.65064   1.186 0.235469    
## Subj_hearing_rating_aided    1.26440    0.83753   1.510 0.131127    
## Subj_hearing_rating_unaided -4.80248    1.26743  -3.789 0.000151 ***
## Tinnitus_past_wk_bin         1.72993    0.98404   1.758 0.078749 .  
## SSQ15i_mean                  0.08561    0.64183   0.133 0.893891    
## SIM_mean                    -0.14577    0.29619  -0.492 0.622615    
## Emocheq_mean                -0.71311    0.77177  -0.924 0.355491    
## HHIES_total                  0.35817    0.13188   2.716 0.006609 ** 
## positive_SCI_bin             0.74498    1.47506   0.505 0.613525    
## CSRQ_mean                   -1.20147    1.28087  -0.938 0.348239    
## Mobility_needs_bin           3.76606    3.13412   1.202 0.229506    
## ABC_mean                    -0.03983    0.09533  -0.418 0.676069    
## SWLS_mean                   -0.25840    0.52024  -0.497 0.619401    
## WHOQOL_overall_qol          -0.83342    0.92690  -0.899 0.368577    
## WHOQOL_health_qol           -1.81784    0.94566  -1.922 0.054570 .  
## WHO_money                    0.55103    0.55792   0.988 0.323319    
## PHQ4_mean                   -1.27155    1.46151  -0.870 0.384289    
## Lonely_bin                  -2.72142    1.68101  -1.619 0.105464    
## Social_network_index         0.82708    0.35702   2.317 0.020523 *  
## Soc_part_freq               -0.96243    0.80039  -1.202 0.229188    
## Soc_part_types              -0.68527    0.44169  -1.551 0.120793    
## Motivate_mean               -0.53730    0.67082  -0.801 0.423160    
## PTA4_better_ear              0.10468    0.07061   1.483 0.138186    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## (Dispersion parameter for binomial family taken to be 1)
## 
##     Null deviance: 317.160  on 245  degrees of freedom
## Residual deviance:  59.256  on 215  degrees of freedom
## AIC: 121.26
## 
## Number of Fisher Scoring iterations: 9
With missing data imputation (n=525)

Significant predictors: Subj_vision_rating_aided, Subj_hearing_rating_unaided, Tinnitus_past_wk_bin, HHIES_total, PTA4_better_ear

“Borderline”: Emocheq_mean

##                           term      estimate   std.error   statistic        df
## 1                  (Intercept)  0.7099298119 0.427590265  1.66030396  19.52395
## 2                   Gender_bin  0.0379102617 0.040586547  0.93405979  32.64963
## 3                          Age  0.0020794484 0.002419673  0.85939233 161.92456
## 4                  Retired_bin  0.0348938908 0.034727332  1.00479619 324.90659
## 5                Volunteer_rec -0.0146770924 0.020653726 -0.71062684 116.29450
## 6              Lives_alone_bin -0.0013293405 0.044594500 -0.02980952  34.86516
## 7           Phys_health_rating  0.0235154439 0.025161770  0.93457036 340.21224
## 8         Multimorbidity_score  0.0080939353 0.008192223  0.98800231  49.56151
## 9     Subj_vision_rating_aided  0.0523675355 0.021821709  2.39979071 338.27996
## 10   Subj_hearing_rating_aided  0.0146752705 0.028726996  0.51085294  10.83156
## 11 Subj_hearing_rating_unaided -0.2235336361 0.031317784 -7.13759434  17.56214
## 12        Tinnitus_past_wk_bin  0.1323700886 0.034484599  3.83852772 107.15377
## 13                 SSQ15i_mean -0.0060635793 0.013426847 -0.45160112 194.15172
## 14                    SIM_mean  0.0018748161 0.008739200  0.21452950  41.40915
## 15                Emocheq_mean -0.0374399307 0.020435921 -1.83206480 179.37327
## 16                 HHIES_total  0.0067603410 0.003038584  2.22483270  51.07739
## 17            positive_SCI_bin  0.0137610662 0.052693748  0.26115178 369.14409
## 18                   CSRQ_mean -0.0094620895 0.050446754 -0.18756588  68.34825
## 19          Mobility_needs_bin  0.1013811405 0.078915752  1.28467560 279.61267
## 20                    ABC_mean  0.0015764352 0.001573811  1.00166737 201.20502
## 21                   SWLS_mean -0.0106246817 0.019549489 -0.54347618  69.90539
## 22          WHOQOL_overall_qol -0.0005018867 0.039673266 -0.01265050  28.85071
## 23           WHOQOL_health_qol -0.0344836751 0.021676616 -1.59082370 274.34265
## 24                   WHO_money  0.0227800828 0.021335015  1.06773219  32.93603
## 25                   PHQ4_mean -0.0491196776 0.045483446 -1.07994626  35.29514
## 26                  Lonely_bin -0.0673929501 0.047807373 -1.40967693  66.62459
## 27        Social_network_index  0.0044710001 0.013797135  0.32405280 117.95596
## 28               Soc_part_freq -0.0050696977 0.026897683 -0.18848083 138.87030
## 29              Soc_part_types -0.0048532026 0.012875520 -0.37693254  78.48268
## 30               Motivate_mean -0.0254518356 0.018183903 -1.39969049 366.91367
## 31             PTA4_better_ear  0.0113530427 0.002067921  5.49007436  59.07400
##            p.value
## 1  0.1128295622527
## 2  0.3571300944617
## 3  0.3913945954169
## 4  0.3157427253118
## 5  0.4787382246249
## 6  0.9763889570944
## 7  0.3506726072902
## 8  0.3279506080679
## 9  0.0169446192010
## 10 0.6197048583372
## 11 0.0000013784760
## 12 0.0002097205527
## 13 0.6520604244966
## 14 0.8311871534972
## 15 0.0686001338052
## 16 0.0305366796645
## 17 0.7941210951214
## 18 0.8517726964903
## 19 0.1999689228947
## 20 0.3177073846139
## 21 0.5885309756394
## 22 0.9899937056994
## 23 0.1128008802340
## 24 0.2934052665623
## 25 0.2874907755576
## 26 0.1632861827149
## 27 0.7464719606668
## 28 0.8507748952463
## 29 0.7072409846903
## 30 0.1624509260467
## 31 0.0000008886159